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--- |
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license: mit |
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base_model: microsoft/speecht5_tts |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: ceb_b32_le4_s8000 |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# ceb_b32_le4_s8000 |
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This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3991 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0001 |
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- train_batch_size: 16 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 32 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 2000 |
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- training_steps: 8000 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:--------:|:----:|:---------------:| |
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| 0.4691 | 9.9010 | 500 | 0.4229 | |
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| 0.4352 | 19.8020 | 1000 | 0.4041 | |
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| 0.424 | 29.7030 | 1500 | 0.4032 | |
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| 0.4091 | 39.6040 | 2000 | 0.4037 | |
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| 0.4032 | 49.5050 | 2500 | 0.3995 | |
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| 0.3877 | 59.4059 | 3000 | 0.4005 | |
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| 0.3794 | 69.3069 | 3500 | 0.3979 | |
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| 0.3755 | 79.2079 | 4000 | 0.4074 | |
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| 0.3694 | 89.1089 | 4500 | 0.3979 | |
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| 0.3559 | 99.0099 | 5000 | 0.4004 | |
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| 0.3633 | 108.9109 | 5500 | 0.4046 | |
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| 0.3557 | 118.8119 | 6000 | 0.3987 | |
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| 0.3548 | 128.7129 | 6500 | 0.3986 | |
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| 0.3465 | 138.6139 | 7000 | 0.3982 | |
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| 0.3403 | 148.5149 | 7500 | 0.4006 | |
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| 0.34 | 158.4158 | 8000 | 0.3991 | |
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### Framework versions |
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- Transformers 4.41.0.dev0 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.19.0 |
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- Tokenizers 0.19.1 |
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